RSTGen: Imbuing Fine-Grained Interpretable Control into Long-Form Text Generators (2022)
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.18653/v1/2022.naacl-main.133
Publication URI: https://api.elsevier.com/content/abstract/scopus_id/85138371306
Type: Other
Parent Publication: NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference